
CoViAR_SEG5_MODEL=../pytorch-coviar/out/cnn_seg5/weights
NAME=freezecnn_lstm_seg5_base5
NAME=cnnlrx10_lstm_seg5
LOG=./out/$NAME/log
MODEL=./out/$NAME/weights

CUDA_VISIBLE_DEVICES=1,2 \
python train.py --arch resnet152 --data-name ylimed \
    --data-root  $ROOT \
    --train-list $TrainSplit \
    --test-list  $PosValSplit \
    --representation iframe \
    --model-prefix $MODEL/ylimed \
    --lr      0.0003 \
    --lstm_lr 0.0003 \
    --batch-size 32 \
    --lr-steps 40 80 \
    --epochs 90 \
    --num_segments 5 \
    --freeze \
    --weights $CoViAR_SEG5_MODEL/ylimed_iframe_model_best.pth.tar \
    --gpus 0 1 > $LOG/ylimed_iframe_model.out 2>&1 &

CUDA_VISIBLE_DEVICES=3 \
python train.py --arch resnet18 --data-name ylimed \
    --data-root  $ROOT \
    --train-list $TrainSplit \
    --test-list  $PosValSplit \
    --representation mv \
    --model-prefix $MODEL/ylimed \
    --lr      0.005 \
    --lstm_lr 0.005 \
    --batch-size 80 \
    --lr-steps 80 120 \
    --epochs 160 \
    --num_segments 5 \
    --freeze \
    --weights $CoViAR_SEG5_MODEL/ylimed_mv_model_best.pth.tar \
    --gpus 0 > $LOG/ylimed_mv_model.out 2>&1 &

CUDA_VISIBLE_DEVICES=3 \
python train.py --arch resnet18 --data-name ylimed \
    --data-root  $ROOT \
    --train-list $TrainSplit \
    --test-list  $PosValSplit \
    --representation residual \
    --model-prefix $MODEL/ylimed \
    --lr      0.001 \
    --lstm_lr 0.001 \
    --batch-size 80 \
    --lr-steps 80 110 \
    --epochs 130 \
    --num_segments 5 \
    --freeze \
    --weights $CoViAR_SEG5_MODEL/ylimed_residual_model_best.pth.tar \
    --gpus 0 > $LOG/ylimed_residual_model.out 2>&1 &
